In spite of improvements in detection, treatment, and prevention techniques, dental caries remains a widely prevalent condition affecting people of all age groups. If not properly and promptly treated, caries can lead to permanent tooth damage and even to loss of teeth.
Traditional methods for caries detection include visual examination and tactile probing with a sharp dental explorer device, often assisted by radiographic (x-ray) imaging. Detection using these methods can be somewhat subjective, varying in accuracy due to many factors, including practitioner expertise, location of the infected site, extent of infection, viewing conditions, accuracy of x-ray equipment and processing, and other factors. There are also hazards associated with conventional detection techniques, including the risk of damaging weakened teeth and spreading infection with tactile methods as well as exposure to x-ray radiation. By the time caries is evident under visual and tactile examination, the disease is generally in an advanced stage, requiring a filling and, if not timely treated, possibly leading to tooth loss.
In response to the need for improved caries detection methods, there has been considerable interest in improved imaging techniques that do not employ x-rays. One method that has been commercialized employs fluorescence, caused when teeth are illuminated with high intensity blue light. This technique, termed quantitative light-induced fluorescence (QLF), operates on the principle that sound, healthy tooth enamel yields a higher intensity of fluorescence under excitation from some wavelengths than does de-mineralized enamel that has been damaged by caries infection. The strong correlation between mineral loss and loss of fluorescence for blue light excitation is then used to identify and assess carious areas of the tooth. A different relationship has been found for red light excitation, a region of the spectrum for which bacteria and bacterial by-products in carious regions absorb and fluoresce more pronouncedly than do healthy areas.
It is recognized that, with fluorescence techniques, the image contrast that is obtained corresponds to the severity of the condition. Accurate identification of caries using these techniques often requires that the condition be at a more advanced stage, beyond incipient or early caries, because the difference in fluorescence between carious and sound tooth structure is very small for caries at an early stage. In such cases, detection accuracy using fluorescence techniques may not show marked improvement over conventional methods. Because of this, the use of fluorescence effects appears to have some practical limits that prevent accurate diagnosis of incipient caries. As a result, a caries condition may continue undetected until it is more serious, requiring a filling, for example.
Detection of caries at very early stages is of particular interest for preventive dentistry. As noted earlier, conventional techniques generally fail to detect caries at a stage at which the condition can be reversed. As a general rule of thumb, incipient caries is a lesion that has not penetrated substantially into the tooth enamel. Where such a caries lesion is identified before it threatens the dentin portion of the tooth, remineralization can often be accomplished, reversing the early damage and preventing the need for a filling. More advanced caries, however, grows increasingly more difficult to treat, most often requiring some type of filling or other type of intervention.
In order to take advantage of opportunities for non-invasive dental techniques to forestall caries, it is desirable that caries be detected at the onset. In many cases, this level of detection has been found to be difficult to achieve using existing fluorescence imaging techniques, such as QLF. As a result, early caries can continue undetected, so that by the time positive detection is obtained, the opportunity for reversal using low-cost preventive measures can be lost.
In commonly-assigned U.S. Patent Application Publication No. 2008/0056551, a method and apparatus that employs both the reflectance and fluorescence images of the tooth is used to detect caries. It employs observed back-scattering, or reflectance, for incipient caries and in combination with fluorescence effects, to provide an improved dental imaging technique to detect caries. The technique, referred to as Fluorescence Imaging with Reflectance Enhancement (FIRE), promotes the contrast of images over that of earlier approaches, and to detect incipient caries at stages when preventive measures are likely to take effect. Advantageously, FIRE detection can be accurate at an earlier stage of caries infection than has been exhibited using existing fluorescence approaches that measure fluorescence alone. The application describes a downshifting method to generate the FIRE image.
Commonly-assigned copending PCT/CN2009/000078, entitled METHOD FOR DETECTION OF CARIES describes a morphological method for generating a FIRE image with reduced sensitivity to illumination variation.
The tooth surface itself is complex. Buccal and lingual surfaces of the tooth are characteristically smooth, with a contour that changes gradually from one side of the tooth to the other. Occlusal surfaces, on the other hand, are typically pitted and have significant number of transitions in slope and contour over the tooth surface. As a result of these differences in surface characteristics, the same types of image processing and analysis techniques often do not work equally well with both types of tooth surface. The characteristic appearance of caries areas along buccal or lingual surfaces can differ in significant ways from caries occlusal surfaces. These dissimilar types of surfaces can respond differently with respect to contrast of caries regions and specular reflection, for example. Hypo-mineralization and other effects can confuse image processing algorithms designed to detect suspicious caries areas.
In addition to caries detection, characterization of the tooth surface can also be useful for other types of intraoral and dental image processing, including processing that relates to tooth shade and appearance, for example, and for overall classification of intraoral images.
Thus, it can be seen that it would be helpful to classify tooth surface type before attempting to apply caries detection techniques as well as for other processing. This added step in image analysis can help to improve the accuracy of caries detection and reduce the number of false positives.